Health information management : journal of the Health Information Management Association of Australia最新文献

Background: Improving the quality of coded data requires the identification and evaluation of the root causes of clinical coding problems to inform appropriate solutions.

Objective: The objective of this study was to identify the root causes of clinical coding problems.

Method: Twenty-one clinical coders from three cities in Iran were interviewed. The five formal categories in Ishikawa's cause-and-effect diagram were applied as pre-determined themes for the data analysis.

Results: The study indicated 16 root causes of clinical coding problems in the five main themes: (i) policies, protocols, and processes (lack of clinical documentation guidelines; lack of audit of clinical coding and feedback to clinical coders; the long interval between documentation and clinical coding; and not using coded data for reimbursement; (ii) individual factors (shortage of clinical coders; low-skilled clinical coders; clinical coders' insufficient communication with physicians; and the lack of continuing education; (iii) equipment and materials (incomplete medical records; lack of access to electronic medical records and electronic coding support tools; (iv) working environment (lack of an appropriate, dynamic, and motivational workspace; and (v) management factors (mangers' inattention to the importance of coding and clinical documentation; and to providing the required staff support.

Conclusion: The study identified 16 root causes of clinical coding problems that stand in the way of clinical coding quality improvement.

Implications: The quality of clinical coding could be improved by hospital managers and health policymakers taking these problems into account to develop strategies and implement solutions that target the root causes of clinical coding problems.

Background: With increasing implementation of enhanced recovery programs (ERPs) in clinical practice, standardised data collection and reporting have become critical in addressing the heterogeneity of metrics used for reporting outcomes. Opportunities exist to leverage electronic health record (EHR) systems to collect, analyse, and disseminate ERP data. Objectives: (i) To consolidate relevant ERP variables into a singular data universe; (ii) To create an accessible and intuitive query tool for rapid data retrieval. Method: We reviewed nine established individual team databases to identify common variables to create one standard ERP data dictionary. To address data automation, we used a third-party business intelligence tool to map identified variables within the EHR system, consolidating variables into a single ERP universe. To determine efficacy, we compared times for four experienced research coordinators to use manual, five-universe, and ERP Universe processes to retrieve ERP data for 10 randomly selected surgery patients. Results: The total times to process data variables for all 10 patients for the manual, five universe, and ERP Universe processes were 510, 111, and 76 min, respectively. Shifting from the five-universe or manual process to the ERP Universe resulted in decreases in time of 32% and 85%, respectively. Conclusion: The ERP Universe improves time spent collecting, analysing, and reporting ERP elements without increasing operational costs or interrupting workflow. Implications: Manual data abstraction places significant burden on resources. The creation of a singular instrument dedicated to ERP data abstraction greatly increases the efficiency in which clinicians and supporting staff can query adherence to an ERP protocol.

Background: Clinical quality registries provide rich and useful data for clinical quality monitoring and research purposes but are susceptible to data quality issues that can impact their usage. Objective: This study assessed the concordance between comorbidities recorded in the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry and those in state-based hospital admission datasets. Method: All patients in New South Wales, South Australia, Tasmania, Victoria and Western Australia recorded in ANZDATA as requiring chronic kidney replacement therapy (KRT) between 01/07/2000 and 31/12/2015 were linked with state-based hospital admission datasets. Coronary artery disease, diabetes mellitus, cerebrovascular disease, chronic lung disease and peripheral vascular disease recorded in ANZDATA at each annual census date were compared overall, over time and between different KRT modalities to comorbidities recorded in hospital admission datasets, as defined by the International Classification of Diseases (ICD-10-AM), using both the kappa statistic and logistic regression analysis. Results: 29, 334 patients with 207,369 hospital admissions were identified. Comparison was made at census date for every patient comparison. Overall agreement was "very good" for diabetes mellitus (92%, k = 0.84) and "poor" to "fair" (21-61%, k = 0.02-0.22) for others. Diabetes mellitus recording had the highest accuracy (sensitivity 93% (±SE 0.2) and specificity 93% (±SE 0.2)), and cerebrovascular disease had the lowest (sensitivity 54% (±SE 0.2) and specificity 21% (±SE 0.3)). The false positive rates for cerebrovascular disease, peripheral vascular disease and chronic airway disease ranged between 18 and 33%. The probability of a false positive was lowest for kidney transplant patients for all comorbidities and highest for patients on haemodialysis. Conclusions and Implications: Agreement between the clinical quality registry and hospital admission datasets was variable, with the prevalence of comorbidities being higher in ANZDATA.

Background: People are increasingly using the Internet to retrieve health information about chronic musculoskeletal conditions, yet content can be inaccurate and of variable quality.

Objective: To summarise (i) comprehensiveness, (ii) accuracy and clarity, iii) quality of information about treatment choices, (iv) credibility and (v) readability of online information about knee osteoarthritis.

Method: Systematic appraisal of website content. Searches for "knee osteoarthritis" and "knee arthritis" were performed using Google and Bing (October 2020). The top 20 URLs of each search were screened for eligibility. Comprehensiveness, accuracy and clarity of content were matched against 14 pre-defined topic descriptors. DISCERN and HONcode were used to measure quality of information about treatment choices and website credibility, respectively. Flesch Reading Ease and Flesch-Kincaid Grade Level tests were used to assess readability.

Results: Thirty-five websites were included. Websites were generally comprehensive (median, range = 12, 0-14/14) with descriptors available for 67% (n = 330/490) of topics across all websites, but only 35% (n = 116/330) were accurate and clear. Quality of information about treatment choices was generally low (median DISCERN score, range = 40, 16-56/80). Credibility descriptors were present for 65% (n = 181/280) of items, with 81% (n = 146/181) of descriptors being clear. Median Flesch reading ease was 53 (range = 21-74), and Flesch-Kincaid grade level was 8 (range = 5-11).

Conclusion: Few websites provide accurate and clear content aligned to key research evidence. Quality of information about treatment choices was poor, with large variation in comprehensiveness, credibility and readability.

Implications: Careful consideration is required by clinicians to identify what online information people with knee osteoarthritis have accessed and to address misinformed beliefs.

Background: Lymphoedema is a condition of localised swelling caused by a compromised lymphatic system. The protein-rich fluid accumulating in the interstitial tissue can create inflammation and irreversible changes to the skin and underlying tissue. An array of methods has been used to assess and report these changes. Heterogeneity is evident in the clinic and in the literature for the domains assessed, outcomes and outcome measures selected, measurement protocols followed, methods of analysis, and descriptors used to report change. Objective: This study seeks consensus on the required items for inclusion in a core data set for upper limb lymphoedema to digitise the monitoring and reporting of upper limb lymphoedema. Methods: The breadth of outcomes and descriptors in common use were captured in prior studies by this research group. This list was refined by frequency and proposed to experts in the field (n = 70) through a two-round online modified Delphi study. These participants rated the importance of each item for inclusion in the dataset and identified outcomes or descriptors they felt were missing in Round 1. In Round 2, participants rated any new outcomes or descriptors proposed and preference for how numeric data is displayed. Results: The core dataset was confirmed on completion of Round 2. Interlimb difference as a percentage, and limb volume were preferred for graphed display over time; and descriptors for observed and palpated change narrowed from 42 to 20. Conclusion: This dataset provides the foundation to create a clinical support system for upper limb lymphoedema.

Background: Access to accurate and relevant patient health information is crucial for community pharmacists to deliver high-quality care. The use of electronic patient medication records (e-PMR) in the United Arab Emirates (UAE) is currently limited to hospital settings, and community pharmacists do not have access to patient records.

Objective: To evaluate the perceptions of community pharmacists regarding the potential benefits, barriers, and concerns associated with the implementation of the e-PMR system in community pharmacies in the UAE.

Method: A validated questionnaire was administered to a sample of licensed community pharmacists using proportionate random sampling. The survey was structured and consisted of 40 questions in four sections: characteristics of community pharmacists and pharmacies; perceived usefulness of e-PMR; perceived barriers; and concerns about the use of e-PMR.

Results: In total, 552 pharmacists filled out the questionnaire (82.1% response rate). The majority of participants somewhat or strongly agreed that e-PMR would reduce drug abuse (71.6%), dispensing errors (64.4%) and prescribing errors (69.0%), and believed that e-PMR would enhance pharmacists' ability to perform medication reviews (76.0%). Pharmacists in charge (adjusted odds ratio (AOR) = 2.5; 95% confidence interval (CI): 1.6-3.6), facing difficulty tracking the medical history of patients (AOR = 3.2; 95% CI: 2.8-3.9) and working in pharmacies providing telepharmacy services (AOR = 3.4; 95% CI: 2.7-3.8) were more likely to consider e-PMR useful.

Implications: The implementation of the e-PMR system in community pharmacies has potential benefits for patient safety and medication therapy management in the UAE.

Background: One of the challenges when transitioning from International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) to International Classification of Diseases, 11th Revision (ICD-11) is to ensure clinical coding accuracy.

Objective: To determine the accuracy of clinical coding with ICD-11 in comparison with ICD-10 and identify causes of coding errors in real clinical coding environments.

Method: The study was conducted prospectively in two general hospitals. Medical records of discharged inpatients were coded by hospital clinical coders with both ICD-11 and ICD-10 on different days. These medical records were recoded by five mentors. Codes assigned by mentors were used as the gold standard for the evaluation of accuracy.

Results: The accuracy of ICD-10 and ICD-11 coding for 1578 and 2168 codes was evaluated. Coding accuracy was 89.1% and 74.2% for ICD-10 and ICD-11. In ICD-11, the lowest accuracy was observed in chapters 22 (injuries), 10 (ear) and 11 (circulatory) (51.1%, 53.8% and 62.7%, respectively). In both ICD-10 and ICD-11, the most important cause of the coding errors was clinical coders' mistakes (79.5% and 81.8% for ICD-10 and ICD-11, respectively).

Conclusion: Accuracy of clinical coding with ICD-11 was lower relative to ICD-10. Hence, it is essential to carry out initial preparations, particularly the training of clinical coders based on their needs, as well as the necessary interventions to enhance the documentation of medical records according to ICD-11 before or simultaneous with the country-wide implementation.

Implications: Clinical coders need complete training, especially in using extension codes and post-coordination coding. Local ICD-11 guidelines based on the needs of local users and reporting policies should be developed. Furthermore, documentation guidelines based on ICD-11 requirements should be developed.

Background: Career success can be defined as the accomplishment of desirable outcomes in an individual's work experiences. It can be divided into objective and subjective career success. Objective success refers to tangible and measurable outcomes such as promotions and position titles. Subjective career success relates to an individual's interpretations of their success or accomplishments. The career success of health information management professionals has not been explored in the literature.

Aim: To determine the indicators of career success as reported by health information managers (HIMs) and identify whether there are any differences based on length of time in the profession.

Methods: Using a cross-sectional study design, an online survey was administered to a sample of La Trobe University and Lincoln Institute of Health Sciences Medical Record Administration and Health Information Management graduates from 1985, 1995, 2005 and 2015, which included the following question: "How would you define success in your career?"

Results: Almost 88% (n = 63) of overall participants in the study responded to this item. Subjective factors (n = 77) of career success, compared to objective factors (n = 22), were more common. The categories of recognition (feeling valued/appreciated), job satisfaction and feelings of accomplishment/sense of achievement were commonly reported.

Discussion: Subjective factors of an individual's career success were deemed to be more significant than objective factors among HIMs.

Conclusion: Factors such as recognition and appreciation at work, job satisfaction, fostering high-quality work outputs and creating a sense of achievement should be the major foci for managers, organisations and individuals.

Objective: To map clinical registries within the Central Adelaide Local Health Network (CALHN); and to identify how these registries were currently used for addressing unwarranted clinical variation in care.

Method: An online survey was sent to all Heads of Units (HoUs) within CALHN. The survey addressed participation, type of data, reporting processes and use of the clinical registries for research, quality assurance (QA), quality improvement (QI) and clinical variation in health care.

Results: Twenty-six HoUs responded (26%); 25 contributed to a clinical registry (96%); all provided data to more than one registry, but only 34.6% had an existing financial and governance arrangement with the network. Health outcomes were the most common datapoints; 77% of all data were collected manually; and 38.5% of data analysis was risk adjusted. Access to aggregated data varied across the registries; and 65.4% of reports included benchmarks and outliers. Clinical registries were used for research in 65.4%, and QA and QI in 73.1 and 69.2%, respectively. Most used external comparators and measured clinical variation, but there was marked inconsistency in the exploring clinical variation, improving care and reporting activities.

Conclusion: Based on this sample, clinical registries within CALHN did not currently appear to be a reliable resource to consistently address unwarranted clinical variation but were shown to be valuable resources for research and quality initiatives at a high level. Further research is required to facilitate effective integration of clinical registries with administrative and quality systems.

Background: Accurate coded diagnostic data are important for epidemiological research of stroke.

Objective: To develop, implement and evaluate an online education program for improving clinical coding of stroke.

Method: The Australia and New Zealand Stroke Coding Working Group co-developed an education program comprising eight modules: rationale for coding of stroke; understanding stroke; management of stroke; national coding standards; coding trees; good clinical documentation; coding practices; and scenarios. Clinical coders and health information managers participated in the 90-minute education program. Pre- and post-education surveys were administered to assess knowledge of stroke and coding, and to obtain feedback. Descriptive analyses were used for quantitative data, inductive thematic analysis for open-text responses, with all results triangulated.

Results: Of 615 participants, 404 (66%) completed both pre- and post-education assessments. Respondents had improved knowledge for 9/12 questions (p < 0.05), including knowledge of applicable coding standards, coding of intracerebral haemorrhage and the actions to take when coding stroke (all p < 0.001). Majority of respondents agreed that information was pitched at an appropriate level; education materials were well organised; presenters had adequate knowledge; and that they would recommend the session to colleagues. In qualitative evaluations, the education program was beneficial for newly trained clinical coders, or as a knowledge refresher, and respondents valued clinical information from a stroke neurologist.

Conclusion: Our education program was associated with increased knowledge for clinical coding of stroke. To continue to address the quality of coded stroke data through improved stroke documentation, the next stage will be to adapt the educational program for clinicians.